Typically, lenders, such as banks, credit card companies and the like, offer loans to consumers based upon a calculation of the rate of return for loans given a certain level of risk. Because this calculation is a highly subjective process, lenders will ensure that loans are appropriately priced for a large pool of applicants to ensure that a minimum return will be met for over all loans. Therefore, the credit process begins with a formulation of strategy on how to allocate credit among customers and products to obtain the highest level of return for a given level of risk. This is generally a very structured, quantitative process where credit scores are calculated to estimate the expected default rate of a customer based on data from loan applications and credit bureaus. Credit products are then structured having a limited set of terms and pricing points depending upon an individual customer's credit score, so that groups of customers having similar credit scores will receive the same loan terms. Thus, the conventional wisdom is to price pools of loans and recoup returns by selling products in large volume.
A problem with such conventional methods and systems for offering loans is that less creditworthy customers tend to apply in greater numbers. Therefore, credit products must be priced to cover this phenomenon so that a return is ensured despite the potential of default for a large number of customers. Therefore, credit terms are typically priced so that customers with higher credit scores subsidize the less creditworthy customers. This typically makes a product less attractive to customers having higher credit, which amplifies the problem, as less favorable credit terms are generally unattractive to those with high credit.
What is therefore needed are systems, methods and computer program products for determining and setting loan terms for each individual customer to cover that customer's risk, so that creditworthy customers are not given unattractive terms to subsidize less creditworthy customers.